Method and system for manufacturing semiconductor devices, and method and system for inspecting semiconductor devices

ABSTRACT

The present invention relates to a method of inspecting a product, comprising extracting defects from the product, classifying the defects on the basis of information about the extracted defects representing the analogy of the defects, extracting the feature data of the defects on the basis of the result of defect classification, and feeding back the feature data of the extracted defects for inspection; and to an inspection system comprising an inspecting means for extracting defects from the product, a defect classifying means for classifying the defects on the basis of information about the defects extracted by the inspecting means representing the analogy of the defects, and a feature data extracting means for extracting the feature data of the defects on the basis of the result of defect classification provided by the defect classifying means, characterized in that the feature data of the defects extracted by the feature data extracting means is fed back to the inspecting means for inspecting the product.  
     The present invention relates also to a method of manufacturing a semiconductor device or the like, comprising extracting defects from the semiconductor device or the like, classifying the defects on the basis of information about the extracted defects representing the analogy of the defects, extracting the feature data of the defects on the basis of the result of defect classification, and feeding back the feature data of the extracted defects to an apparatus for manufacturing the semiconductor device or the like.

BACKGROUND OF THE INVENTION

[0001] The present invention relates to a method and system forefficiently manufacturing semiconductor devices or the like with highreliability and an inspection method and system for inspecting thesemiconductor devices.

[0002] A conventional manufacturing process control system controls amanufacturing process on the basis of data obtained through theautomatic inspection and repair of products. When the manufacturingprocess control system inspects products by an automatic inspectingsystem, the parameters of defect identifying standards to be used by theautomatic inspection system are changed properly to enhance thereliability of inspection when the automatic inspection system providesexcessively large amount of false information regarding nondefectiveproducts as defective or when residual defect ratio is excessivelylarge.

[0003] A product inspected by the automatic inspection system and provedto be nondefective is sent to the next process, and repairable defectiveproducts are sent to a repairing process and are sent to the nextprocess after being repaired. The operator monitors the condition of themanufacture of products statistically and, when necessary, changes theparameters for controlling the condition of the manufacturing machinesto regulate the condition of the manufacturing process.

[0004] More concretely, in a semiconductor manufacturing process,presumably defective products found by using a visual inspectioninstrument, such as disclosed in Japanese Patent Laid-open (Kokai) No.61-151410 or No. 62-43505, or a foreign matter inspection instrument,such as disclosed in Japanese Patent Laid-open (Kokai) No. 54-101390,for specifying presumably defective products are examined visually bymeans of a microscope included in the inspection instrument or aseparate microscope to classify defects including foreign matters anddefective patterns, and false information. A method of classifyingdetected defects using a multifocus image is disclosed in JapanesePatent Laid-open (Kokai) No. 2-170279.

[0005] Recently, Galai Laboratory of Israel and ADE Co. of the U.S.A.published cooperatively an automatic classification technique (M. Luria,E. Adin, M. Moran, D. Yaffe and J. Kawaski, “Automatic DefectClassification Using Fuzzy Logic”, ASMC '93 Boston Mass., 1993), thedetails of which is unknown. Results of classification of defects areanalyzed, manufacturing machines presumably causative of defects arespecified on the basis of the results of analysis and results ofinspection carried out in other processes. Skilled members of the staffof the manufacturing process relevant to the specified manufacturingmachine adjust the parameters for controlling the manufacturing machineand correct the manufacturing machine on the basis of their experiences.

[0006] In a manufacturing process for manufacturing thin-film transistorwafer for liquid crystal displays, short circuit defects are detected byusing a short circuit inspecting instrument, such as disclosed inJapanese Patent Laid-open (Kokai) No. 4-72552, the short circuit defectsare confirmed visually, and the short circuit defects are classified bycauses including particles, aluminum residues and through holes.

[0007] The foregoing prior art designed for the automation of inspectionor the automation of inspection and repair for a system for controllingmanufacturing processes on the basis of the results of automaticinspection and repair of products has the following problems. The priorart automatic inspection system consists of a detecting system fordetecting defects in the product, and an information processing systemfor analyzing information provided by the detecting system to seewhether or not the product has defects and to classify defects bycategory. Therefore, when the quality of the product varies according tothe variation of the manufacturing process within an allowable range andthe automatic inspection system decides that the product is defective,the automatic inspection system needs readjustment.

[0008] Since the detection system and the information processing systemare the inherent components of the automatic inspection system asmentioned above, it is difficult to alter the detection system and theinformation processing system substantially. Accordingly, thesensitivity of the like of the detecting system or parameters forcontrolling the information processing system is changed for thereadjustment of the automatic inspection system. In most cases, thereadjustment of the automatic inspection system to adjust the inspectioncriteria of the automatic inspection system to inspecting standards usedin the manufacturing process is carried out by a trial-and-error methodat the site of manufacture, which takes much time to make the automaticinspection apparatus function normally. If the automatic inspectionsystem is an in-line inspecting apparatus, the operation of theassociated production line must be suspended during the adjustment ofthe automatic inspection system.

[0009] Another automatic inspection system inspects a product to seewhether or not the product is defective and, if the product has adefect, provides only information about the position of the defect inthe product. When this automatic inspection system is used, defects mustbe classified by the operator, and it is possible to examine theparameters of the automatic inspection system to see if the parametersare proper only after the classification and analysis of the defects bythe operator. Therefore, the automatic inspection system not only needsmuch time before the same starts normally functioning, the inspectionsystem has the possibility of inspecting products according toinappropriate inspecting standards while the defects are beingclassified and analyzed.

[0010] Accordingly, if the automatic inspection system is not adjustedproperly, products are inspected and repaired erroneously.

[0011] In the prior art automatic inspection system, nothing isconsidered about means for making the operator make a decision aboutwhether or not correction is necessary, i.e., whether or not the defectsare classified correctly, to control a correcting operation and forfeeding back information about the results of examination of the resultsof defect classification made by the automatic inspection system by theoperator to the automatic inspection system.

[0012] Similarly, when defect detection information provided by theautomatic inspection system in an imperfectly adjusted condition is usedas means for adjusting the manufacturing machine for manufacturing theproducts, it is impossible to adjust the parameters for controlling theoperating condition of the manufacturing machine for properlymanufacturing the products. Since correcting information produced on thebasis of the results of inspection provided by the automatic inspectionsystem is fed back to the automatic inspection system, the completereadjustment of the automatic inspection system takes much time.

[0013] Furthermore, although accurate information about defects inproducts and information about the working condition of a manufacturingprocess are necessary for securing the stability of the manufacturingprocess, it requires much time to examine the correlation between themanufacture of defective products and the condition of the manufacturingprocess, because the accurate analysis of defects and the readjustmentof the manufacturing process are carried out simultaneously when theproducts are inspected by the aforesaid prior art automatic inspectionsystem.

[0014] Still further, since the prior art automatic inspection systemdoes not attach the results of inspection and the bases of the resultsof inspection to the inspected product, it is impossible to find whichmanufacturing process is causative of the defect or the causalrelationship between a defect detected at the final stage of manufactureand a defect detected at the middle stage of manufacture is unknown evenif the defect is detected by inspection in the next process or by finalinspection.

SUMMARY OF THE INVENTION

[0015] It is an object of the present invention to provide an adjustingmeans capable of properly and quickly adjusting inspecting standards onthe basis of which an automatic inspection system functions, incooperation with the operator to thereby provide a method ofmanufacturing a semiconductor device or the like, capable of enablingautomatic inspection and automatic repair, a manufacturing system forcarrying out the method, an inspection method, and an inspection systemfor carrying out the inspection method.

[0016] With the foregoing object in view, the present invention providesthe following means.

[0017] (A) An inspection system in a first aspect of the presentinvention comprises: an automatic inspection unit for inspecting aproduct according to predetermined inspecting standards and extractingdefects in the product; a defect classifying and feature extracting unitfor receiving information about the extracted defects provided by theautomatic inspection unit, classifying the defects by category,providing the results of classification of the defects and extractingthe feature data of the defects on the basis of the results ofclassification; and a feature data converting unit for converting thefeature data into corresponding inspecting standards for the automaticinspection unit and feeding back inspecting standards obtained byconversion to the automatic inspection unit.

[0018] (B) An inspection system in a second aspect of the presentinvention comprises: an automatic inspection unit for inspecting aproduct according to predetermined inspecting standards and extractingdefects in the product; a defect classifying and feature extracting unitfor receiving information about the extracted defects provided by theautomatic inspection unit, classifying the defects by category,providing the results of classification of the defects and extractingthe feature data of the defects on the basis of the results ofclassification; and a feature-parameter conversion unit for convertingthe feature data into parameters for controlling the condition of themanufacturing machine manufacturing the product, and feeding back theparameters obtained by conversion to the manufacturing machine to adjustthe manufacturing machine.

[0019] (C) The defect classifying and feature extracting unit stated in(A) or (B) is provided with a teaching means capable of teaching acorrect result of defect classification when the result of defectclassification provided by the defect classifying and feature extractingunit is incorrect.

[0020] (D) The inspecting system stated in (A) or (B) is provided withan information showing means capable of visually showing the result ofdefect classification provided by the defect classifying and featureextracting unit to the operator to enable the operator recognize theresult of defect classification and information relating thereto, and tochange the information or add new information to the information.

[0021] (E) The inspecting system includes an information storage meansfor storing the information mentioned in (D) and information about eachdefect.

[0022] (F) The inspection system is capable of extracting the featuredata of defects from a plurality of pieces of the information mentionedin (D) and stored in the information storage means mentioned in (E) andinformation about the defects in the product corresponding to theinformation mentioned in (D), the feature data is given to the featuredata converting unit mentioned in (A), and amends the inspectingstandards to be used by the automatic inspection unit mentioned in (A).

[0023] (G) The inspection system is capable of extracting the featuredata of defects from a plurality of pieces of the information mentionedin (D) stored in the information storage means mentioned in (E) and theinformation about the defects in the product, gives the feature data tothe feature-parameter conversion unit mentioned in (B) and adjusts themanufacturing machine mentioned in (B).

[0024] (H) The inspection system is capable of adding information aboutthe manufacturing process in a condition where the defects have justdeveloped to the information mentioned in (D) stored in the informationstorage means mentioned in (E) and the information about the defects inthe product corresponding to the information mentioned in (D), andholding and presenting the condition of the manufacturing process andhistorical information about the mode of development of defects inconnection with each other.

[0025] (I) The inspection system includes a teaching means capable ofshowing the information about the defects and the related informationincluding information about the category of an unknown defect when thedefect classifying and feature extracting unit mentioned in (A) or (B)is unable to classify the results of classification of defects in theproduct into existing categories, and of enabling the operator to assigna new or an existing category, a name and the like to the defect of anunknown category.

[0026] (J) The information about the defect mentioned in (E), (F), (G),(H) and (I) is an image information about the defect and a regionsurrounding the defect.

[0027] (K) The product inspected by the automatic inspection unit (1)stated in (A) is sent to a product repair unit according to the resultof defect classification provided by the defect classifying and featureextracting unit mentioned in (A) or (B), and the product is subjected toa predetermined repairing work.

[0028] (L) The product repairing operation of the product repair unitmentioned in (K) can be controlled by the operator, and the productrepair unit is capable of teaching a correct result of defectclassification when the result of defect classification provided by thedefect classifying and feature extracting unit mentioned in (A) or (B)is incorrect and of feeding back the information about the correctresult of defect classification to the defect classifying and featureextracting unit.

[0029] (M) Pattern information about an image of a detected defect isused as the attribute of the defect mentioned in (A) or (B).

[0030] (N) Signal information about the information about the detecteddefect is used as the attribute of the defect mentioned in (A) or (B).

[0031] (O) Information about either the result of inspection of theproduct or the result of measurement of the product, or both the resultof inspection of the product and the result of measurement of theproduct is attached to the product.

[0032] (P) A manufacturing machine presumably causative of the defect isselected in view of the result of deflect classification provided by thedefect classifying and feature extracting unit mentioned in (B) and theattribute of the defect, and the feature data of the defect extracted bythe defect classifying and feature extracting unit mentioned in (B) issent to the feature-parameter conversion unit mentioned in (B).

[0033] Naturally, the inspection system is independent of the foregoingautomatic inspection unit. However, the automatic inspection unit may bea unit provided with a monitoring apparatus for monitoring the conditionof a product, capable of inspection or monitoring and incorporated intoa manufacturing machine.

[0034] The operation of the foregoing means to achieve the object of theinvention will be explained hereinafter with reference to FIG. 1.

[0035] A thick line 12 represents the flow of a product in amanufacturing process. An automatic inspection unit 1 inspects a productand extracts defects according to predetermined inspecting standards. Adefect classifying and feature extracting unit 2 classifies defects andextracts the feature data of the defects.

[0036] The automatic inspection unit 1 gives defect information aboutthe defects detected through inspection to the defect classifying andfeature extracting unit 2. The defect information includes images of thedefects, electric signals generated upon the detection, information onthe basis of which the defects are identified, and the like. The defectclassifying and feature extracting unit 2 classifies the defects on thebasis of the defect information. The defects are classified on the basisof various feature data on a rule basis or a model basis. A defectclassification indicating unit 6 indicates the result of defectclassification to enable the correction of the result of defectclassification.

[0037] The defect classification indicating unit 6 shows the result ofdefect classification visually to enable an operator to recognizeinformation including the result of defect classification and therelated information and to change the information or add new informationthereto.

[0038] The defect classifying and feature extracting unit 2 changes theinterpretation of the feature data of the corresponding defect on thebasis of the result of defect classification taught thereto by thedefect classification indicating unit 6.

[0039] A feature data converting unit 3 is capable of converting thefeature data of the defects classified by the defect classifying andfeature extracting unit 2 into inspecting standards. The feature dataconverting unit 3 sends the inspecting standard obtained by convertingthe feature data to the automatic inspection unit 1. If the result ofdefect classification provided by the defect classifying and featureextracting unit 2 and the result of a decision made by the automaticinspection unit 1 are different from each other, the result of defectclassification provided by the defect classifying and feature extractingunit 2 is reflected through the feature data converting unit 3 on theautomatic inspection unit 1.

[0040] A feature-parameter conversion unit 4 is capable of convertingthe feature data of the defects classified by the defect classifying andfeature extracting unit 2 into control parameters relating tomanufacturing conditions for a product manufacturing machine 8 formanufacturing the product. The feature-parameter conversion unit 4 givesthe control parameters obtained by converting the feature data to theproduct manufacturing machine 8. The defect classifying and featureextracting unit 2 is capable of selecting the product manufacturingmachines 8 to be readjusted on the basis of the result of defectclassification and of sending information to the feature-parameterconversion units 4 connected to the selected product manufacturingmachines 8.

[0041] An information storage unit 7 connected to the defect classifyingand feature extracting unit 2 stores all or part of defect informationabout each of the defects in the product received from the automaticinspection unit 1, the result of defect classification received from thedefect classifying and feature extracting unit 2, information used fordefect classification, and, when the defect classifying and featureextracting unit 2 is provided with a means for obtaining imageinformation or electric signals, image information or electric signalsabout defects in the product, regions surrounding the defects or otherportions characterizing the defects, which are different from theinformation obtained by the automatic inspection unit 1.

[0042] The defect classifying and feature extracting unit 2 is capableof receiving information about the operating condition of the productmanufacturing machines 8. The information received by the defectclassifying and feature extracting unit 2 is stored in addition to theinformation about the product in the information storage unit 7. Theinformation about the defects and the like stored in the informationstorage unit 7 is subjected to statistical data processing whennecessary and the statistically processed information is shown to theoperator by the defect classification indicating unit 6 connected to thedefect classifying and feature extracting unit 2. All or part of theinformation about each of the defects stored in the information storageunit 7 and the information provided by the defect classifying andfeature extracting unit 2 are sent to a process control system 5.

[0043] A product sorting unit 9 selects defective products which are tobe repaired and delivers the selected defective products onto a repairline 13 to send the defective products to relevant repair units 11according to instructions given thereto from the defect classifying andfeature extracting unit 2.

[0044] The repair units 11 may be substituted by a single repair unitcapable of removing all kinds of defects or each of the repair units 11may be capable of removing a specific defect. Although the repair units11 are capable of automatic repairing operation, they enable theoperator to determine whether or not repair is necessary, and, when thecategory of the defect is different from that determined by the defectclassifying and feature extracting unit 2, they are capable of informingthe defect classifying and feature extracting unit 2 to that effect.

[0045] An information attaching unit 14 attaches information about theresult of inspection of the product by the automatic inspection unit 1and the associated information to the product.

[0046] With the inspection system thus constructed efficient inspectionof products is made possible for manufacturing products with highreliability according to the manufacturing process.

[0047] The present invention has the following advantages.

[0048] (A) Since the inspecting standards by which the automaticinspection unit inspects products can be automatically readjusted by thedefect classifying and feature extracting unit 2 of FIG. 1 or can besemiautomatically readjusted through the feature data converting unit 3of FIG. 1 under operator's supervision using the defect classificationindicating unit 6 connected to the defect classifying and featureextracting unit 2, the inspecting standards can be readjusted toinspecting standards conforming to the process conditions withoutstopping the automatic inspection unit.

[0049] (B) Since the inspecting standards can be automaticallyreadjusted by the defect classifying and feature extracting unit 2 ofFIG. 1 or can be semiautomatically readjusted through the feature datacomparing unit 3 of FIG. 1 under operator's supervision using the defectclassification indicating unit 6 connected to the defect classifying andfeature extracting unit 2, the inspecting reliability of the automaticinspection unit can be improved quickly.

[0050] (C) The effect mentioned in (A) curtails the time necessary forstarting up the automatic inspection unit when products of one kindbeing inspected are changed for those of another kind.

[0051] (D) Since the effect mentioned in (A) curtails the time necessaryfor adjusting the automatic inspection unit, the number of productswhich are inspected on the basis of inappropriate inspecting standardscan be reduced.

[0052] (E) Since the classification of defects by the defect classifyingand feature extracting unit 2 of FIG. 1 enables the categories ofdefects to be known and thereby the manufacturing machines presumablycausative of the defects can be determined. The manufacturing processcan be stabilized quickly by adjusting the manufacturing machines takinginto consideration the characteristic defects of the manufacturingmachines through the operation of the feature-parameter conversion unit4 of FIG. 1.

[0053] (F) The effect mentioned in (B) enables correct instructions tobe given to the repairing process, so that the incorrect repair ofproducts can be prevented.

[0054] (G) The defect classifying and feature extracting unit 2 of FIG.1 is adjusted while defects are removed by operating a defectclassification input unit 10 connected to the repair unit 11 of FIG. 1and, consequently, the inspecting standards by which the automaticinspection unit inspects products can be readjusted.

[0055] (H) The defect classification indicating unit 6 processes theinformation stored in the information storage unit 7 of FIG. 1 andindicates the processed information to enable the operator to graspeasily the relation between the causes of defects and the condition ofthe manufacturing process.

[0056] (I) Information given to the information storage unit 7 of FIG. 1is transferred to the process control system 5 of FIG. 1 to enable thecontrol of the condition of the entire manufacturing process.

[0057] (J) When the result of defect classification provided by thedefect classifying and feature extracting units 2 of the automaticinspection units installed respectively at different positions in themanufacturing process and the feature data of defects are compared andwhen the result of defect classification provided by the defectclassifying and feature extracting units 2 are similar to each other, aportion of the manufacturing process between the automatic inspectionunits connected to those defect classifying and feature extracting units2 need not be monitored and hence either of the upstream and downstreamautomatic inspection units of the manufacturing process may be omitted.The automatic inspection units can thus be installed at optimumpositions in the manufacturing process.

[0058] (K) Since the information attaching unit 14 of FIG. 1 attachesthe result of inspection and the associated information to the inspectedproduct, the manufacturing processes causative of the defects and thecausal relation between defects detected by inspection at the finalstage and those detected at the middle stage can be known by comparingthe information attached to the product and the result of inspection inthe following manufacturing processes or the result of final inspection.

BRIEF DESCRIPTION OF THE DRAWINGS

[0059]FIG. 1 is a block diagram for the concept of the presentinvention;

[0060]FIG. 2 is a block diagram of a semiconductor device manufacturingprocess incorporating the present invention;

[0061]FIG. 3 is a block diagram of a defect classifying and featureextracting unit for classifying defects and extracting the feature dataof defects;

[0062]FIG. 4 is a conceptual block diagram for explaining a defectclassifying method;

[0063]FIG. 5 is a diagrammatic view showing the distribution of defectclusters;

[0064]FIG. 6 is a perspective view of a terminal equipment, showinginformation displayed on a screen;

[0065]FIG. 7 is a perspective view of a terminal equipment, showinginformation displayed on a screen;

[0066]FIG. 8 is a block diagram of a cause determining unit;

[0067]FIG. 9 is a conceptual block diagram of assistance in explaining aprocedure for determining causes of defects;

[0068]FIG. 10 is a conceptual block diagram of a cause model;

[0069]FIG. 11 is a conceptual block diagram of assistance in explaininga method of adjusting and controlling an inspection unit;

[0070]FIG. 12 is a conceptual block diagram of assistance in explaininga method of adjusting and controlling a film forming apparatus;

[0071]FIG. 13 is a conceptual block diagram of assistance in explaininga method of adjusting and controlling an exposure unit;

[0072]FIG. 14 is a conceptual block diagram for explaining a method ofadjusting and controlling a developing unit;

[0073]FIG. 15 is a conceptual block diagram for explaining a method ofadjusting and controlling an etching unit;

[0074]FIG. 16 is a schematic view for explaining a method of adjustingand controlling a dry etching unit;

[0075]FIG. 17 is a diagram of for explaining a method of adjusting andcontrolling an etching unit when the etching unit malfunctions;

[0076]FIG. 18 is a schematic perspective view for explaining a method ofadjusting and controlling a CVD system;

[0077]FIG. 19 is a schematic perspective view for explaining theprinciple of detecting foreign matters on a wafer;

[0078]FIG. 20 is a graph of data obtained by inspecting a wafer carrying1 μm standard particles;

[0079]FIG. 21 is a graph of data obtained by inspecting a wafer carrying2 μm standard particles;

[0080]FIG. 22 is a graph of data obtained by inspecting a wafer carrying1 μm standard particles;

[0081]FIG. 23 is a graph of data obtained by inspecting a wafer carrying1 μm standard particles, in which the intensity of the laser beam ishalf that of the laser beam used for obtaining the data shown in FIG.22;

[0082]FIG. 24 is a flow chart of a thin-film transistor wafermanufacturing process;

[0083]FIG. 25 is a typical wiring diagram of the electricalconfiguration of a thin-film transistor wafer;

[0084]FIG. 26 is a block diagram of a short circuit inspecting andrepairing apparatus having a defect classifying function; and

[0085]FIG. 27 is a flow chart of a repairing procedure to be carried outby the short circuit inspecting and repairing apparatus of FIG. 26.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0086] First, the conceptual intention of the present invention will bedescribed with reference to FIG. 1 prior to the description of thepreferred embodiments of the present invention.

[0087] A thick line 12 represents the flow of a product in amanufacturing process. An automatic inspection unit 1 inspects a productand extracts defects according to predetermined inspecting standards. Adefect classifying and feature extracting unit 2 classifies defects andextracts the feature data of the defects. The automatic inspection unit1 gives defect information about the defects detected through inspectionto the defect classifying and feature extracting unit 2. The defectinformation includes images of the defects, electric signals generatedupon the detection of the defects, information on the basis of which thedefects are identified, and the like.

[0088] The defect classifying and feature extracting unit 2 classifiesthe defects on the basis of the defect information. The defects areclassified on the basis of various feature data on a rule basis or amodel basis. A defect classification indicating unit 6 indicates theresult of defect classification to enable the correction of the resultof defect classification. The defect classification indicating unit 6shows the result of defect classification visually to enable theoperator to recognize information including the result of defectclassification and the related information and to change the informationor add new information to the information. The defect classifying andfeature extracting unit 2 changes the interpretation of the feature dataof the corresponding defects on the basis of the result of defectclassification taught thereto by the defect classification indicatingunit 6.

[0089] A feature data converging unit 3 is capable of converting thefeature data of the defects classified by the defect classifying andfeature extracting unit 2 into inspecting standards. The feature dataconverting unit 3 sends the inspecting standards obtained by convertingthe feature data to the automatic inspection unit 1. If the result ofdefect classification provided by the defect classifying and extractingunit 2 and the result of a decision made by the automatic inspectionunit 1 are different from each other, the result of defectclassification provided by the defect classifying and feature extractingunit 2 is reflected through the feature data converting unit 3 on theautomatic inspection unit 1.

[0090] A feature-parameter conversion unit 4 is capable of convertingthe feature data of the defects classified by the defect classifying andfeature extracting unit 2 into control parameters relating tomanufacturing conditions for a product manufacturing machine 8. Thefeature-parameter conversion unit 4 gives control parameters obtained byconverting the feature data to the product manufacturing machine 8. Thedefect classifying and feature extracting unit 2 is capable of selectingthe product manufacturing machine 8 to be readjusted on the basis of theresult of defect classification and of sending information to thefeature-parameter conversion unit 4 connected to the selected productmanufacturing machine 8.

[0091] An information storage unit 7 connected to the defect classifyingand feature extracting unit 2 stores all or part of defect informationabout each of the defects in the product received from the automaticinspection unit 1, the result of defect classification received from thedefect classifying and feature extracting unit 2, information used fordefect classification, and, when the defect classifying and featureextracting unit 2 is provided with a means for obtaining imageinformation or electric signals, image information or electric signalsabout defects in the products, regions surrounding the defects or otherportions characterizing the defects, which are different from theinformation obtained by the automatic inspection unit 1.

[0092] The defect classifying and feature extracting unit 2 is capableof receiving information about the operating condition of the productmanufacturing machine 8. The information received by the defectclassifying and feature extracting unit 2 is stored in addition to theinformation about the product in the information storage unit 7. Theinformation about the defects and the like stored in the informationstorage unit is subjected to statistical data processing when necessaryand the statistically processed information is shown to the operator bythe defect classification indicating unit 6 connected to the defectclassifying and feature extracting unit 2. All or part of theinformation about each of the defects stored in the information storageunit 7 and the information provided by the defect classifying andfeature extracting unit 2 are sent to a process control system 335 ofFIG. 2.

[0093] A product sorting unit 9 selects defective products which are tobe repaired and delivers the selected defective products onto a repairline 13 to send the defective products to relevant repair units 11according to instructions given thereto from the defect classifying andfeature extracting unit 2.

[0094] The repair units 11 may be substituted by a single repair unitcapable of removing all kinds of defects or each of the repair units 11may be capable of repairing a specific defect. Although the repair units11 are capable of automatic repairing operation, they enable theoperator to determine whether or not repair is necessary, and, when thecategory of the defect is different from that determined by the defectclassifying and feature extracting unit 2, they are capable of informingthe defect classifying and feature extracting unit 2 to that effect.

[0095] An information attaching unit 14 attaches information about theresult of inspection of the product by the automatic inspection unit 1and the associated information to the product.

[0096]FIG. 2 shows an inspection system in a first embodiment accordingto the present invention as applied to a semiconductor wafermanufacturing process. Briefly, the semiconductor wafer manufacturingprocess comprises a series of steps of forming a film on a wafer by afilm forming unit 321, exposing the film to light in a pattern by anexposure unit 322, developing the film in the pattern by a developingunit 323, etching by an etching unit 324, and the series of steps isrepeated a plurality of times to form stacked layers in patterns on thewafer.

[0097] While a plurality of cycles of the semiconductor wafermanufacturing process are repeated, an inspection unit 320 inspectsproducts by a sampling inspection method or a total inspection method todetermine the positions of presumed defects for quality control, andsends position information representing the positions of the presumeddefects, detected image information, defect distribution information andthe data of the wafer to a defect classifying and feature extractingunit 300 for classifying defects and extracting feature data of defects.A defect classifying and feature extracting unit 300 a compares theinformation about each presumed defect with a defect model and a defectimage data base for similarity examination to remove false information,and then classifies the defects. A cause determining unit 300 bdetermines causes of the defects on the basis of information about theclassified defects, time series information about distribution obtainedand stored in the past, and the positional distribution of defects.

[0098]FIG. 3 shows the configuration of the defect classifying andfeature extracting unit 300 of FIG. 2. The defect classifying andfeature extracting unit 300 is included in a network including theinspection unit 320, the cause determining unit 300 b, and a terminalequipment 311 for indicating information to the operator, providinginstructions and entering information by the operator, and is capable ofcommunicating image information, defect information, process informationand the like optionally.

[0099] The terminal equipment 11 is provided with a bitmapped display todisplay image information. The terminal equipment 311 may be substitutedby a character terminal equipment and a TV monitor. The defectclassifying and feature extracting unit 300 comprises a control unit301, a data processing unit 302, an image memory 303, a machine controlunit 304 for controlling stages, a detector 347, an illuminating unit341 for illuminating a wafer 360, a half mirror 345, a lens 348, anX-stage 340, a Y-stage 341, a θ-stage 342, a Z-stage 343, an image datastorage unit 350, and a classification model storage unit 352 forstoring classification models of shapes of defects, sizes of defects,colors of defects, positions of defects on wiring patterns, and texturesof defects. The functions of these components may be substituted bythose of the inspection unit 320. The components of the network may beelectrically interconnected by a serial serial transmission system, suchas RS232C, or a parallel transmission system, such as Centronics.

[0100] A defect classifying method to be carried out by the defectclassifying and feature extracting unit 300 will be describedhereinafter with reference to FIG. 4. When the inspection unit 320 findsa defect on the wafer, the detector 347 picks up an image 372 of thedefect. The image is aligned with an image 371 of a nondefective portionof the wafer having the same pattern, i.e., a reference image, thedifference between the image and the reference image is determined by amethod, such as a method published in Denshi Joho Tsushin GakkaiRonbunshi (Journal of Electronic Information Communication Society)D-II, Vol. J72-D-II, No. 12, pp. 2041-2050, the pattern is removed fromthe image and only the image of the defect is extracted to produce adefect image 373.

[0101] Feature data are extracted from information including textureinformation 380, color or density distribution information 381, shapeinformation 382 obtained by detecting the outline information 3-Dinformation obtained by varying focus, area information 383, andposition information 384 about the position of the defect relative tothe nearby wiring pattern provided by the inspection unit 320, andextracted from the defect image 373, and the detected defect is mappedin an n-dimensional feature data space consisting of several-n featuredata.

[0102] Classification models stored in the classification model storageunit 352 define regions corresponding to the feature data of defects inthe n-dimensional space. The detected defect mapped in the n-dimensionalfeature data space is compared with the classification model, falseinformation is removed, and then the defect is classified. Whenclassifying the defect, the defect is identified by clusters defined ina classification space defined by feature data as shown in FIG. 5.Although FIG. 5 shows a two-dimensional space, practically, theclassification space is an n-dimensional space, and the clusters ofdefects are defined by regions in the multidimensional space.

[0103] In FIG. 5, the category of a defect in an overlapping portion,namely, shaded region, of the clusters cannot be identified by a singlecategory, typical defects included respectively in the overlappingclusters are displayed as shown in FIG. 6 to request the operator tospecify the category of the defect. If the defect does not belong to anyone of the clusters, representative defects are displayed in theincreasing order of distance from the classification space as shown inFIG. 7. When one of the displayed defects is specified, an additionalcluster is registered. Even if the category of the defect could beidentified, the cluster can be changed or renewed by the operator.

[0104] Detected pieces of information 380, 381, 382, 383 and 384 arestored as new data of the classification model in the classificationmodel storage unit 352 and, at the same time, the image data 371 and 372are stored additionally in the image data storage unit 350 to constructan image date base.

[0105] A defect which cannot be identified is indicated for the operatorby the terminal equipment 311 and is added to the image data base and isregistered as a classification model. The detected pieces of information380, 381, 382, 383 and 384 are stored as the data of new classificationmodels in the classification model storage unit 352. The image datacorresponding to the data of the new classification models is added tothe contents of the image data storage unit 350 to construct an imagedata base. A defect which cannot be identified is indicated for theoperator by the terminal equipment 311 and is added to the image database and is registered as classification model.

[0106] Although the foregoing description is based on an assumption thatthe comparison is made in the n-dimensional feature data space, thecomparison may be made on the basis of the correlation between the imageof the defect, and a representative defect mode contained in the imagedata base or a plurality of images of defects, using the image data basestored in the image data storage unit 350.

[0107] When storing an image in the image data storage unit 350, datarepresenting the condition of the manufacturing process, i.e.,parameters for controlling a wafer manufacturing apparatus, which willbe described later, and information about other inspection units ormonitors are stored in the image data storage unit 350.

[0108] The foregoing procedure for defect classification and featuredata extraction can be repeatable whenever necessary by reading theimage data because the image data 371 and 372 of defects are held by theimage data storage unit 350. Since the condition of the manufacturingprocess at that time can be read from the image data storage unit 350and can be displayed on the terminal equipment 311, both the defects andthe condition of the manufacturing process can be known.

[0109] The result of defect classification and the feature datainformation on which defect classification is based are given to thecause determining unit 300 b. FIG. 8 shows the configuration of thecause determining unit 300 b. The cause determining unit 300 b comprisesa control unit 361, a data processing unit 362, and cause models 363 tobe used for determining causes of defects from the result of defectclassification. The control unit 301 and the data processing unit 302 ofthe classifying unit 300 of FIG. 3 may be used as the control unit 361and the data processing unit 362, and the cause models 363 may beconnected to the control unit 301.

[0110] Referring to FIG. 9, when determining the cause of a defect, theresult of defect classification provided by the classifying unit 300 andthe feature data information on which defect classification is based arecompared with the cause models 390 to identify the cause of the defect.If the cause of the defect cannot be identified, information isindicated to that effect on the terminal equipment 311 and a new causemodel is registered. The cause models 390 are those as shown in FIG. 10.Information about the cleanliness of the entire manufacturing process,time series defect information and the distribution of defects are usedin combination with the result of classification of individual defectsto specify an apparatus causative of the defect, and the result ofdefect classification and the feature data information on which thedefect classification is based are given to machine parameter adjustingunits 331, 332, 333 and 334, which will be described later. The sameinformation is given to an inspection parameter adjusting unit 330 forthe adjustment of the inspecting standards for the operation of theinspection unit.

[0111] The inspection parameter adjusting unit 330 for converting theresult of defect classification and the feature data information onwhich defect classification is based into inspecting standards for theinspection unit, and the machine parameter adjusting units 331, 332, 333and 334 for converting the same information into control parameters forcontrolling the manufacturing machine will be described below.

[0112] Referring to FIG. 11, when the inspection unit does not leave anydefect undetected but many pieces of false information are provided, theinspection parameter adjusting unit 330 adjusts process parameters so asto meet the level of the machine. If much false information isattributable to mechanical troubles, an indication is displayed to thateffect on the terminal equipment 311 to the operator. If the inspectionunit leaves some defects undetected, the inspection parameter adjustingunit 330 adjusts the thresholds of the inspecting standards. If failurein detection of defects is attributable to the defocusing of the imagesensing unit of the detector, the inspection parameter adjusting unit330 adjusts focusing parameters. If illumination is causative of failurein detection of defects, the inspection parameter adjusting unit 330adjusts the luminance of the illuminating unit 346.

[0113] When the defect is caused by the film forming unit 321, themachine parameter adjusting unit 331 converts the result of defectclassification and the feature data information on which defectclassification is based into control parameters as shown in FIG. 12 forcontrolling the manufacturing machine, and the film forming unit 321 isadjusted and controlled.

[0114] When the defect is caused by the exposure unit 322, the machineparameter adjusting unit 332 converts the result of defectclassification and the feature data information on which defectclassification is based into control parameters as shown in FIG. 13 forcontrolling the manufacturing machine, and the exposure unit 322 isadjusted and controlled. If the defect is caused by a mechanicalmalfunction, the parameters are not adjusted and information that thereis mechanical trouble is indicated on the terminal equipment 311 toprompt the operator to repair the relevant machine.

[0115] When the defect is caused by a defective mask, the terminalequipment 311 prompts the operator to change the defective mask,instructions about measured to remove causative foreign matters andflaws are given to the operator, information is given to the processcontrol system 335 to that effect and, if the adhesion of the foreignmatters to the mask is due to the condition of the entire process, acontrol process control system provides instructions to clean the wholemanufacturing process.

[0116] When the defect is caused by the developing unit 323, the machineparameter adjusting unit 331 converts the result of defectclassification and the feature data information on which defectclassification is based into parameters as shown in FIG. 14 forcontrolling the manufacturing machine to adjust and control thedeveloping unit 323.

[0117] When the defect is caused by causes as shown in FIG. 15 in theetching unit, the machine parameter adjusting unit 334 adjusts theconcentration of the solution if the etching unit is of a wet etchingsystem or the flow rates of gases are adjusted through the machineparameter adjusting unit 334 by flow regulators 3341, 3342 and 3343 ifthe etching unit is of a dry etching system as shown in FIG. 16.

[0118] As shown in FIG. 17, the distribution of particles, i.e., foreignmatters, introduced into the product by the etching unit is differentfrom that of particles introduced into the product in a steady state;that is, particles are distributed in a narrow range of particle size,so that it can easily be determined that the etching unit introducedthose particles into the product. In such a case, the machine parameteradjusting unit 334 gives an order to wash the interior of the etchingunit with pure water, and then the etching unit is evacuated for selfcleaning. It is also possible to make such a determination on the basisof the shape and the distribution on the product of particles.

[0119] In a CVD system as shown in FIG. 18, the machine parameteradjusting unit gives information to a flow regulator and a pressureregulator to control the flow rates and the pressures of the gases.

[0120] Naturally, plans for the maintenance of and conditions for theoperation of the manufacturing machines including an annealing unit, anion implantation unit, an evaporating unit and an electrical inspectionunit as well as the aforesaid manufacturing machines can be worked outon the basis of the result of defect classification and informationextracted from the classified defects by the aforesaid methods.

[0121] There have been described above about the functions of theinspection parameter adjusting unit 330 for converting the result ofdefect classification and the feature data information on which defectclassification is based into inspecting standards for discriminatingbetween defective and nondefective products by the inspection unit, andthe machine parameter adjusting units 331, 332, 333 and 334 forconverting the same information into control parameters for controllingthe manufacturing machines. The result of defect classification and thefeature data information on which defect classification is based may bedefect categories and parameters of feature data models stored in theclassification model storage unit 352. When the defect categories andthe parameters of feature data models are used, stable, highly accuratestatistical information can be given to the inspection parameteradjusting unit 330 and the machine parameter adjusting units 331, 332,333 and 334, and hence the manufacturing process can be maintained in afurther stable state.

[0122] When the results of inspection or information on which inspectionis based is engraved in the marginal areas of each wafer or each chipwith, for example, a laser beam, by an information attaching unit 399 ofFIG. 2, investigation into causes of defects developed between thesuccessive testing processes is possible. If the information is engravedon each chip, investigation into the correlation between the results ofelectrical inspection, such as inspection for fail bits after dicing,and defects attributable the manufacturing process is possible.

[0123] An inspection system in a second embodiment according to thepresent invention including an automatic inspection unit for detectingforeign matters adhering to semiconductor wafers employing an inventiondisclosed in Japanese Patent Laid-open (Kokai) No. 54-101390 will bedescribed hereinafter.

[0124] Referring to FIG. 19 showing the principle of detection accordingto the aforesaid disclosed invention, a laser light source 501 projectS-polarized laser beam 502 on the surface of a semiconductor wafer 500,i.e., a product, so that the laser beam 502 falls on the surface of thesemiconductor wafer 500 at an angle nearly equal to zero to the surfaceof the semiconductor wafer 500. The laser beam 502 reflected verticallyupward is detected by a detector 503. The major component of the laserbeam scattered by a pattern formed on the semiconductor wafer 500 isS-polarized laser beam and the minor component of the same isP-polarized laser beam, where as the most component of laser beamscattered by a particle adhering to the wafer is P-polarized laser beam.The vertically reflected laser beam is focused on the detector 503 witha focusing lens 504.

[0125] In FIG. 19, broken lines indicate the laser beam scattered by thepattern formed on the semiconductor wafer 500, and continuous linesindicate scattered laser beam scattered by the particle adhering to thesemiconductor wafer 500. Most part of the laser beam scattered by thepattern and traveled through the focusing lens 504 is intercepted by apolarizing plate 507 for selectively absorbing S-polarized laser beam,so that the detector 503 is able to detect only the laser beam scatteredby the particle adhering to the semiconductor wafer 500 in a highaccuracy. A signal processing circuit 508 processes the output signalsof the detector 503 to detect the particle. Upon the detection of theparticle, the signal processing circuit 508 provides a position signalrepresenting the position of the particle on the semiconductor wafer500.

[0126]FIG. 20 is a graph typically showing distribution curves ofdetected luminance levels determined by inspecting the surface of awafer carrying a 1 μm standard particle by the foregoing inspectingmethod. Indicated at 510 is a cluster of a pattern formed on the waferand at 511 is a cluster of the 1 μm standard particle. Although theluminance of the beam scattered by the pattern formed on the wafer anddetected by the detector is low, a comparatively high peak appears at acomparatively low luminance level because the ratio of the surface areaof the pattern to the surface area of the wafer is greater than that ofthe particle. On the other hand, although the ratio of the surface areaof the 1 μm standard particle to the surface area of the wafer is small,the distribution of the luminance of the scattered light scattered bythe 1 μm standard particles, i.e., a foreign matter, has a comparativelylow peak at a comparatively high luminance level because the luminanceis high.

[0127]FIG. 21 is a graph typically showing distribution curves ofdetected luminance levels determined by inspecting the surface of awafer carrying a 2 μm standard particle. Since the scattering area ofthe 2 μm standard particle is greater than that of the 1 μm standardparticle, the luminance level at which a peak appears in thedistribution curve for the 2 μm standard particle is higher than that atwhich a peak appears in the distribution curve for the 1 μm standardparticle. Accordingly, when it is desired to detect only foreign mattersof sizes greater than a given size, a threshold luminance level is set.If a threshold luminance level TH as shown in FIGS. 20 and 21 is set,only foreign matters of sizes not smaller than 2 μm can be detected. Thethreshold luminance level TH is determined according to the size offoreign matters to be detected for process control. The thresholdluminance level TH is a control parameter for controlling thesensitivity of the foreign matter detector.

[0128] The sensitivity can be controlled by controlling the detectionsystem; that is, when the current supplied to a driver for driving thelaser beam source is controlled to regulate the intensity of the laserbeam emitted by the laser beam source, the detection luminance level canbe regulated accordingly, which will be explained with reference toFIGS. 22 and 23.

[0129]FIG. 22, similarly to FIG. 20, is a graph typically showingdistribution curves of detected luminance levels determined byinspecting the surface of a wafer carrying a 1 μm standard particle bythe foregoing inspecting method, in which a current I₀ was supplied tothe driver for controlling the laser beam source.

[0130]FIG. 23 is a graph typically showing distribution curves ofdetected luminance levels determined by inspecting the surface of awafer carrying a 1 μm standard particle when a current I₁ that makes thelaser beam source emit laser beam of an intensity half the intensity oflaser beam emitted by the laser beam source when a current I₁ issupplied to the driver is supplied to the driver.

[0131] As shown in FIGS. 22 and 23, the central value 518 of a cluster517 of a pattern formed on a wafer is half the central value 514 of acluster 513 of the pattern, and the central values 520 of a cluster 519of the 1 μm standard particle is half the central value 516 of a cluster515 of the 1 μm standard particle, because the intensity of the laserbeam is reduced by half and the detected luminous level is reducedaccordingly when the current I supplied to the driver for controllingthe laser beam source is reduced from I₀ to I₁. Therefore, when a fixedthreshold luminance level TH is given as shown in FIGS. 22 and 23, aforeign matter of a size can be detected when the current supplied tothe driver for controlling the laser beam source is I₀ and the sameparticle cannot be detected when the current I₁ is supplied to thedriver. Thus, the detection sensitivity of the detector can be regulatedby regulating the current supplied to the driver for controlling thelaser beam source. The detection sensitivity can be regulated also byregulating the gain of the detector.

[0132] The defect classifying and feature extracting unit 2 (FIG. 1)reads an image of the semiconductor wafer, i.e., the product, on thebasis an output of the automatic inspection unit representing thecoordinates of the position of the foreign matter on the semiconductorwafer. Since the semiconductor wafer has a plurality of identicalnondefective chips or a plurality of identical nondefective patterns inaddition to the identical defective chip or the identical defectivepattern, an image of the nondefective chip or the nondefective patternis used as a reference image, the reference image is subtracted from theimage of the defective chip or the defective pattern by the methoddisclosed in Denshi Joho Tsushin Gakkai Ronbunshi (Journal of ElectronicInformation Communication Society) D-II, Vol. J72-D-II, No. 12, pp.2041-2050 to extract only the image of the foreign matter, and then thearea of the image of the foreign matter is measured to determine thesize of the foreign matter. This procedure is carried out for theoutputs of the automatic inspection unit provided by detecting onesemiconductor wafer, and then the sizes of foreign matters areclassified to determine the distribution of the sizes of the foreignmatters.

[0133] In view of this result, the operator operates the defectclassification indicating unit 6 shown in FIG. 1 connected to the defectclassifying and feature extracting unit to enter the size of a foreignmatter to be detected. The feature data converting unit 3 shown in FIG.1 may be provided with an arithmetic circuit of a processing systemrealizing Z=F(S), where Z is conversion output and S is area, in orderthat the input area is converted into the threshold luminance level THshown in FIGS. 20 and 21, the current for controlling the intensity ofthe laser beam, or the value for controlling the gain of the detector.In another system, the feature data converting unit 3 shown in FIG. 1may be a look-up table that provides an output Z, i.e., the thresholdluminance level TH shown in FIGS. 20 and 21, the current for controllingthe intensity of laser beam or the value for controlling the gain of thedetector, corresponding to the area S.

[0134] When the defect classifying and feature extracting unit 2 shownin FIG. 1 has the function explained in connection with the foregoingexample of inspection of a defect in the pattern formed on a wafer, theextracted information about foreign matters can be applied to themanufacturing process for the same effect.

[0135] An embodiment of the present invention applied to a process ofmanufacturing a thin-film transistor wafer for a liquid crystal displaywill be described hereinafter. FIG. 24 shows a manufacturing process formanufacturing the thin-film transistor wafer. Basically, thismanufacturing process is the same as the semiconductor wafermanufacturing process, except that the inspection step in thismanufacturing process gives priority to the inspection of electriccircuits over the inspection of appearance. All the product is inspectedfor short-circuiting defects and, if the products have defects, thedefective products are repaired. FIG. 25 is a typical wiring diagramshowing the electrical wiring of a thin-film transistor wafer. Thethin-film transistor wafer is provided with gate lines (G-lines) 411 to415, drain lines (D-lines) 421 to 425 extending across and insulatedfrom the G-lines. A thin-film transistor 407 and a transparentphotocathode 408 are formed at each of intersections of the G-lines andthe D-lines.

[0136] The G-lines are connected to a common line 401, and the D-linesare connected to common lines 402 and 403 to prevent electrostaticbreakdown until the thin-film transistor wafer is completed. In thisexample, a short-circuiting defect 404 is the short-circuiting of theG-line and the D-line causing linear faulty indication, which is acritical defect in the thin-film transistor wafer. Therefore, thedetected short-circuiting defect 404 is cut off with a laser beam todisconnect the G-line and the D-line electrically. It is possible thatthe D-lines are short-circuited by a short-circuiting defect. Thisshort-circuit defect is also cut off with a laser beam to disconnect theD-lines electrically.

[0137]FIG. 26 shows a wafer inspecting system for detectingshort-circuiting defects and repairing a short-circuited circuit,capable of defect classification. A thin-film transistor wafer 400 ismounted on a composite stage consisting of a θ-stage 440, a Z-stage 441,a Y-stage 442 provided with a positioning sensor 444, and an X-stage 443provided with a positioning sensor 445. Wafer probers 447 and 448 areapplied respectively to the common lines 401 and 402, the common lines401 and 403 or the common lines 402 and 403 shown in FIG. 25. A voltagecontrol unit 451 controls voltage applied across the wafer probers 447and 448 while current is monitored by an ammeter 446. Heat generated bythe current flowing through the short-circuiting defect 404 is detectedby an infrared detector 430 to measure the radiated infrared rays asimage information. The infrared detector 430 is provided with lenses432, 433 and 434. A desired one of the lenses 432, 433 and 434 can beset at a working position by a revolver 435.

[0138] The image information thus acquired is stored in the image memory452 and processed to determine the position of the short circuit defect404. The stage 443 is moved according to the position information aboutthe position of the short-circuiting defect 404. The defect is observedand the short-circuiting line is cut off by a microscopic laserprocessing unit comprising a detector 431, a half mirror 438, a lens 436and a laser oscillator 437, and serving as a microscope and a laserprocessing device. Feature data is extracted from the image informationobtained by the detector 431 and the image information obtained by theinfrared detector 430, the feature data is compared with aclassification models 456 to determine the type of the defect. Thisprocedure can be achieved by a method similar to the wafer inspectingmethod previously described with reference to FIGS. 4 and 9.

[0139] In the inspection of the thin-film transistor wafer for a liquidcrystal display, which is different from inspection for the observationof appearance, even most visually unobservable short-circuiting defectscan be observed in infrared images. The present invention is applicableto inspection using an optical system using a radiation of a wavelengthdifferent from that of a radiation used by an ordinary optical system.After the category of the defect has been determined, information isgiven to the cause determining unit, information is given to the processcontrol system, the machine parameter adjusting unit and the inspectionparameter adjusting unit, and the stored image data 455 and the storedclassification models 456 are updated. The parameter, such as thedetection wavelength used by the wafer inspecting system, can be changedby the inspection parameter adjusting unit on the basis of the dataprovided by the cause determining unit.

[0140]FIG. 27 shows a repairing procedure to be carried out by the waferinspecting system. The position size and shape of the defect areestimated on the basis of infrared image information, visible imageinformation and leakage current provided by the wafer inspecting system,the criticality of the defect is assessed on the basis of the amount ofgenerated heat and short circuit resistance, and whether or not thedefect is repairable is determined with reference to the classificationmodels 456. The product is rejected if the defect is unrepairable. Ifthe product has a repairable defect, the product is subjected to anautomatic repairing process, in which a position to be irradiated with alaser beam, the length of the slit for the laser beam and the intensityof the laser beam are controlled by the machine parameter adjustingunit.

[0141] The classification models 456 for determining whether or not thedefect is repairable, similarly to those for semiconductor waferinspection, can be updated or new models can be registered by operatingthe terminal equipment. During the repairing operation, the result ofclassification of the defect is displayed for the operator. Therepairing operation is continued if the defect is classified correctly,and a correct classification of the defect is entered by operating theterminal equipment and then the repairing operation is executed. Repairinformation is fed back to the classification models 456 to update theclassification models 456.

[0142] The present invention is applicable also to processes ofsoldering, inspecting soldered parts and repairing soldered parts,processes of mounting electronic parts on a substrate, inspecting theelectronic parts and repairing defective electronic parts, processes ofmanufacturing, inspecting and repairing thick-film and thin-film hybridwafer, processes of manufacturing, inspecting and adjusting CRTs, suchas CDT displays, and processes of electrical inspection ofsemiconductors.

[0143] The present invention has the following advantages.

[0144] (A) Since the inspecting standards of the automatic inspectionunit can be automatically readjusted by the defect classifying andfeature extracting unit 2 of FIG. 1 or can be semiautomaticallyreadjusted through the feature data converting unit 3 of FIG. 1 underoperator's supervision using the defect classification indicating unit 6connected to the defect classifying and feature extracting unit 2, theinspecting standards can be readjusted to inspecting standardsconforming to the process conditions without stopping the automaticinspection unit.

[0145] (B) Since the inspecting standards can be automaticallyreadjusted by the defect classifying and feature extracting unit 2 ofFIG. 1 or can be semiautomatically readjusted through the feature datacomparing unit 3 of FIG. 1 under operator's supervision using the defectclassification indicating unit 6 connected to the defect classifying andfeature extracting unit 2, the inspecting reliability of the automaticinspection unit can be improved quickly.

[0146] (C) The advantage mentioned in (A) curtails time necessary forstarting up the automatic inspection unit when products of one kindbeing inspected are changed for those of another kind.

[0147] (D) Since the advantage mentioned in (A) curtails time necessaryfor adjusting the automatic inspection unit, the number of productswhich are inspected on the basis of inappropriate inspecting standardscan be reduced.

[0148] (E) Since the classification of defects by the defect classifyingand feature extracting unit 2 of FIG. 1 enables the categories ofdefects to be know and thereby the manufacturing machines presumablycausative of the defects can be determined. The manufacturing processcan be stabilized quickly by adjusting the manufacturing machines takinginto consideration the characteristics defects of the manufacturingmachines through the operation of the feature-parameter conversion unit4 of FIG. 1.

[0149] (F) The advantage mentioned in (B) enables correct instructionsto be given to the repairing process, so that the incorrect repair ofproducts can be prevented.

[0150] (G) The defect classifying and feature extracting unit 2 of FIG.1 is adjusted while defects are removed by operating the defectclassification input unit 10 connected to the repair unit 11 of FIG. 1and, consequently, the inspecting standards by which the automaticinspection unit inspects products can be readjusted.

[0151] (H) The defect classification indicating unit 6 processes theinformation stored in the information storage unit 7 of FIG. 1 andindicates the processed information to enable the operator to graspeasily the relation between the causes of defects and the condition ofthe manufacturing process.

[0152] (I) Information given to the information storage unit 7 of FIG. 1is transferred to the process control system 5 of FIG. 1 to enable thecontrol of the condition of the entire manufacturing process.

[0153] (J) When the result of defect classification provided by thedefect classifying and feature extracting unit 2 of the automaticinspection units installed respectively at different positions in themanufacturing process and the feature data of defects are compared andwhen the result of defect classification provided by the defectclassifying and feature extracting unit 2 are similar to each other, aportion of the manufacturing process between the automatic inspectionunits connected to those defect classifying and feature extracting units2 need not be monitored and hence either the automatic inspection uniton the upper side of the portion of the manufacturing process or theautomatic inspection unit on the lower side of the portion of themanufacturing process may be omitted. Therefore, the automaticinspection units can be installed at optimum positions in themanufacturing process.

[0154] (K) Since the information attaching unit 14 of FIG. 1 attachesthe result of inspection and the associated information to the inspectedproduct, the manufacturing processes causative of the defects and thecausal relation between defects detected by inspection at the finalstage and those detected at the middle stage can be known by comparingthe information attached to the product and the result of inspection inthe following manufacturing processes or the result of final inspection.

What is claimed is:
 1. A method of inspecting a product, comprising:extracting defects in a product; classifying the defects by category onthe basis of analogy of the defects with information about the extracteddefects; extracting the feature data of the defects on the basis of theresult of defect classification; and feeding back the feature data aboutthe extracted defects.
 2. An inspection system comprising: an inspectionmeans for extracting defects in a product; a defect classifying meansfor classifying the defects on the basis of the analogy of the extracteddefect with information about the extracted defects; a feature dataextracting means for extracting the feature data of the defects on thebasis of the result of defect classification by the defect classifyingmeans; characterized in that the feature data of the defects extractedby the feature data extracting means is fed back to the inspectingmeans.
 3. An inspection system comprising: an automatic inspection unitthat extracts defect in a product according to predetermined inspectingstandards; a defect classifying and feature extracting unit thatreceives information about the extracted defects from the automaticinspection unit, classifies the defects on the basis of the analogy ofthe defects with information about the defects, provides the result ofdefect classification and extracts the feature data of the defects onthe basis of the result of defect classification; and a feature dataconverting unit that converts the feature date into inspecting standardsto be used by the automatic inspection unit and feeds back theinspecting standards determined by converting the feature data to theautomatic inspection unit to adjust the automatic inspection unit.
 4. Aninspection system according to claim 3 further comprising an instructingmeans for giving instructions to specify the correct result of defectclassification when the result of defect classification provided by thedefect classifying and feature extracting unit is incorrect.
 5. Aninspection system according to claim 3 , wherein the defect classifyingand feature extracting unit has a means for visually indicating theresult of defect classification to the operator to enable the operatorto confirm the result of defect classification and the associatedinformation, and to change the information or to add new information tothe information.
 6. An inspection system according to claim 5 furthercomprising an information storage means for storing the information andinformation about each of the corresponding defects in the product. 7.An inspection system according to claim 5 , characterized by extractingfeature data of the defects from a plurality of pieces of informationstored in the information storage means and information about thecorresponding defects in the product, and sending the feature data tothe feature data converting unit (3).
 8. An inspection system accordingto claim 3 , wherein the defect classifying and feature extracting unithas a means for visually indicating the result of defect classificationto the operator to enable the operator to confirm the result of defectclassification and the associated information, and to change theinformation or to add new information to the information.
 9. A method ofmanufacturing a semiconductor device or the like, comprising: extractingdefects in a semiconductor device or the like; classifying the defectson the basis of the analogy of the defects with information about theextracted defects; extracting the feature data of the defects on thebasis of the result of defect classification; and feeding back thefeature data of the extracted defect to an apparatus for manufacturingthe semiconductor device or the like.
 10. An apparatus for manufacturinga semiconductor device or the like, comprising an inspection system thatextracts defects in a semiconductor device or the like, classifies thedefects by category on the basis of information about the extracteddefects, and extracts the feature data of the defects on the basis ofthe result of defect classification; characterized in that the featuredata of the extracted defects is fed back to a relevant manufacturingmachine.
 11. An apparatus for manufacturing a semiconductor device orthe like, comprising: an automatic inspection unit that extracts defectsin a semiconductor device or the like manufactured by a manufacturingmachine, according to predetermined inspecting standards; a defectclassifying and feature extracting unit (2) that receives informationabout the defects extracted by the automatic inspection unit, classifiesthe defects by category on the basis of the analogy of the defects withinformation about the defects, provides the result of defectclassification, and extracts the feature data of the defects on thebasis of the result of defect classification; a control means thatconverts the feature data into control parameters for controlling thecondition of the manufacturing machine, and controls the manufacturingmachine according to the parameters.
 12. An apparatus for manufacturinga semiconductor device or the like according to claim 11 , wherein thedefect classifying and feature extracting unit has a means capable ofgiving instructions to specify the correct result of defectclassification when the result of defect classification provided by thedefect classifying and feature extracting unit is incorrect.
 13. Anapparatus for manufacturing a semiconductor device or the like accordingto claim 11 , wherein the defect classifying and feature extracting unit(2) has a means capable of visually indicating the result of defectclassification to the operator to enable the operator to confirm theresult of defect classification and the associated information, and tochange the information or to add new information to the information. 14.An apparatus for manufacturing a semiconductor device or the likeaccording to claim 13 further comprising an information storage meansfor storing the information and information about each of thecorresponding defects in the product.
 15. An apparatus for manufacturinga semiconductor device or the like according to claim 13 , capable ofextracting extracting feature data of the defects from the plurality ofpieces of information stored in the information storage means and theinformation about the corresponding defects in the product, andconstructed so as to send the feature data to the feature dataconverting unit.
 16. An apparatus for manufacturing a semiconductordevice or the like according to claim 11 , wherein the defectclassifying and feature extracting unit (2) has a means for visuallyindicating the result of defect classification to the operator to enablethe operator confirm the result of defect classification and theassociated information, and to change the information or to add newinformation to the information.
 17. An apparatus for manufacturing asemiconductor device or the like according to claim 11 , wherein thedefect classifying and feature extracting unit has a means forindicating, when the defect cannot be classified into predeterminedcategories, information about defects and related information to theoperator to that effect to enable the operator to assign a new orpredetermined category, a new or predetermined designation or the liketo the defect of an unknown category.
 18. An apparatus for manufacturinga semiconductor device or the like according to claim 11 , wherein theinformation about the defect is image information about the detecteddefect and a region surrounding the detected defect.
 19. An apparatusfor manufacturing a semiconductor device according to claim 11 , whereinthe defect classifying and feature extracting unit sends the productinspected by the automatic inspection unit to a repairing unit accordingto the result of defect classification, and the product having thedefect is subjected to a predetermined repairing process.
 20. Anapparatus for manufacturing a semiconductor device or the like accordingto claim 19 , wherein the repairing operation of the repairing unit canbe controlled by the operator, information about the correct result ofdefect classification can be given to the repairing unit when the resultof defect classification provided by the defect classifying and featureextracting unit is incorrect, and the information about the correctresult of defect classification can be fed back to the defectclassifying and feature extracting unit.
 21. A method of inspecting aproduct according to claim 1 , wherein pattern information is used forrepresenting the analogy of the defect.
 22. A method of inspecting aproduct according to claim 1 , wherein signal information about defectdetection information is used for representing the analogy of thedefect.
 23. A method of manufacturing a semiconductor device or thelike, characterized by attaching information relating to either theresult of inspection or the result of measurement of a semiconductordevice or the like or both the result of inspection and the result ofmeasurement of the semiconductor device or the like to the inspectedsemiconductor device or the like.
 24. An apparatus for manufacturing asemiconductor device or the like according to claim 11 , wherein thedefect classifying and feature extracting unit selects a manufacturingmachine presumably causative of a defect in consideration of the resultof defect classification and the attribute of the defect, and sends thefeature data of the defect extracted by the defect classifying andfeature extracting unit to the control means.
 25. A method ofmanufacturing a semiconductor device or the like according to claim 9 ,wherein the pattern information about the image of the detected defectis used for representing the attribute of the defect.
 26. A method ofmanufacturing a semiconductor device or the like according to claim 9 ,wherein signal information about the detected defect is used forrepresenting the attribute of the defect.